Search NASA⌕ Search

SEARCH · Search NASA

Results for “statistical physics”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Machine Learning Reveals the State of Intermittent Frictional Dynamics in a Sheared Granular Fault

Seismogenic plate boundaries are posited to behave in a similar manner to a densely packed granular medium, where fault and block systems rapidly rearrange the distribution of forces within themselves, as particles do in slowly sheared granular systems. Machine learning is used to show that statistical features of velocity signals from individual particles in a simulated sheared granular fault contain information regarding the instantaneous global state of intermittent frictional stick-slip dynamics. We demonstrate that combining features built from the signals of more particles can improve the accuracy of the global model and discuss the physical basis behind the decrease in error. We show that the statistical features such as median and higher moments of the signals that represent the particle displacement in the direction of shearing are among the best predictive features. We demonstrate here novel insights into the applications of machine learning in studying frictional processes occurring in geophysical systems.

58 GEOSCIENCES↗
DOE OSTI2022

Sulphur variations in annually layered stalagmites using benchtop micro-XRF

Variation of sulphur in annually laminated stalagmites can be used to infer the impact of past volcanic activities, anthropogenic pollution, and climate change due to increased bushfire activity. The synchrotron radiation micro-X-Ray fluorescence (SR-XRF) microprobe is a powerful tool to analyse and image sulphur recorded in stalagmites with micrometre resolution. However, access to SR-XRF beamlines can be limited, so researchers must select the most promising stalagmites for imaging. Benchtop micro-XRF is an effective tool for trace elemental analysis of speleothem samples and is a candidate for routine laboratory measurement of sulphur along stalagmite laminae and screening for SR-XRF. Here, this study describes a protocol using matrix-matched standards to measure annual variations of sulphur at trace to percent level along the laminae of two Western Australian stalagmites, one of which already having been analysed using SR-XRF. Parameters that affected quantitation include X-ray tube voltage and current, spot size of the X-ray beam and stalagmite surface roughness and porosity. The use of a 20 μm X-ray spot size provides sub-annual spatial resolution that can be completed in an overnight scan. The features in a 1000 point micro-XRF analysis of sulphur along a 20 mm transect show good consistency with SR-XRF microprobe data. Micro-XRF mapping was also performed to produce chemical images on the stalagmite and compared with Raman and X-ray diffraction (XRD) to confirm that the stalagmite is exclusively calcite, with no aragonite, and that the source of sulphur in the samples was gypsum and anhydrite. Regions of very high sulphur in the micro-XRF maps were found to be artefacts due to diffraction of the incident beam but these could be efficiently removed by using a multiple point statistics approach to produce a clean image suitable for analysis of the laminae. This work shows the potential of micro-XRF for routine analysis of sulphur in stalagmites, and to streamline sample characterisation before SR-XRF imaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Monitoring and prediction of porosity in laser powder bed fusion using physics-informed meltpool signatures and machine learning

In this work we accomplished the monitoring and prediction of porosity in laser powder bed fusion (LPBF) additive manufacturing process. This objective was realized by extracting physics-informed meltpool signatures from an in-situ dual-wavelength imaging pyrometer, and subsequently, analyzing these signatures via computationally tractable machine learning approaches. Porosity in LPBF occurs despite extensive optimization of processing conditions due to stochastic causes. Hence, it is essential to continually monitor the process with in-situ sensors for detecting and mitigating incipient pore formation. In this work a tall cuboid-shaped part (10 mm × 10 mm × 137 mm, material ATI 718Plus) was built with controlled porosity by varying laser power and scanning speed. This test caused various types of porosity, such as lack-of-fusion and keyhole formation, with varying degrees of severity in the part. The meltpool was continuously monitored using a dual-wavelength imaging pyrometer installed in the machine. Physically intuitive process signatures, such as meltpool length, temperature distribution, and ejecta (spatter) characteristics, were extracted from the meltpool images. Subsequently, relatively simple machine learning models, e.g., K-Nearest Neighbors, were trained to predict both the severity and type of porosity as a function of these physics-informed meltpool signatures. These models resulted in a prediction accuracy exceeding 95% (statistical F1-score). The same analysis was carried out with a complex, black-box deep learning convolutional neural network which directly used the meltpool images instead of physics-informed features. The convolutional neural network produced a comparable F1-score in the range of 89–97%. Finally, these results demonstrate that using pragmatic, physics-informed meltpool signatures within a simple machine learning model is as effective for flaw prediction in LPBF as using a complex and computationally demanding black-box deep learning model.

36 MATERIALS SCIENCE↗
NASA NTRS1976

On the occurrence of sympathetic flares

Random-coincidence formulas are applied to the data used in previous studies of alleged sympathetic flares to determine whether statistical evidence on the occurrence of such flares can be found for specific physically connected pairs of active regions. Only those active regions that are interconnected by magnetic loops in soft X-rays on Skylab photographs are considered to be physically connected. All pairs of flaring active regions (both interconnected and otherwise) observed on the sun during the Skylab flight are also evaluated. The only positive result is obtained with statistical confidence of 3.4 sigmas for pairs of active regions separated by no more than 30 deg. The occurrence of short time intervals between flares is shown to be increased for such active-region pairs, but the pattern of time intervals is found not to correspond with any propagation mode of a triggering agent in the solar atmosphere. It is suggested that some subphotospheric synchronization of activity in nearby plages and sunspot groups could increase the number of short time intervals between flares at different locations without any actual influence of one 'sympathetic' flare upon another, leading to the concept of 'sympathetic active regions' instead of 'sympathetic flares'.

Fritzova-Svestkova, L.↗
DOE OSTI2017

Statistical Analysis of Hubble /WFC3 Transit Spectroscopy of Extrasolar Planets

Transmission spectroscopy provides a window to study exoplanetary atmospheres, but that window is fogged by clouds and hazes. Clouds and haze introduce a degeneracy between the strength of gaseous absorption features and planetary physical parameters such as abundances. One way to break that degeneracy is via statistical studies. We collect all published HST /WFC3 transit spectra for 1.1–1.65 μ m water vapor absorption and perform a statistical study on potential correlations between the water absorption feature and planetary parameters. We fit the observed spectra with a template calculated for each planet using the Exo-transmit code. We express the magnitude of the water absorption in scale heights, thereby removing the known dependence on temperature, surface gravity, and mean molecular weight. We find that the absorption in scale heights has a positive baseline correlation with planetary equilibrium temperature; our hypothesis is that decreasing cloud condensation with increasing temperature is responsible for this baseline slope. However, the observed sample is also intrinsically degenerate in the sense that equilibrium temperature correlates with planetary mass. We compile the distribution of absorption in scale heights, and we find that this distribution is closer to log-normal than Gaussian. However, we also find that the distribution of equilibrium temperatures for the observed planets is similarly log-normal. This indicates that the absorption values are affected by observational bias, whereby observers have not yet targeted a sufficient sample of the hottest planets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Python GST Implementation v. 0.9 beta

PyGSTi is an implementation of Gate Set Tomography in the python programming language. Gate Set Tomography (GST) is a theory and protocol for simultaneously estimating the state preparation, gate operations, and measurement effects of a physical system of one or many quantum bits (qubits). These estimates are based entirely on the statistics of experimental measurements, and their interpretation and analysis can provide a detailed understanding of the types of errors/imperfections in the physical system. In this way, GST provides not only a means of certifying the "goodness" of qubits but also a means of debugging (i.e. improving) them.

Nielsen, Erik↗
DOE OSTI2015

Python GST Implementation v. 0.9 beta

PyGSTi is an implementation of Gate Set Tomography in the python programming language. Gate Set Tomography (GST) is a theory and protocol for simultaneously estimating the state preparation, gate operations, and measurement effects of a physical system of one or many quantum bits (qubits). These estimates are based entirely on the statistics of experimental measurements, and their interpretation and analysis can provide a detailed understanding of the types of errors/imperfections in the physical system. In this way, GST provides not only a means of certifying the "goodness" of qubits but also a means of debugging (i.e. improving) them.

Nielsen, Erik↗
DOE OSTI2018

Review of Particle Physics

The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,873 new measurements from 758 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Here, among the 118 reviews are many that are new or heavily revised, including a new review on Neutrinos in Cosmology.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2010

Hadron Physics with KLOE and KLOE-2 Experiments

The KLOE experiment has collected 2.5 fb{sup -1} at the peak of the {phi} resonance at the e{sup +}e{sup -} collider DA{Phi}NE in Frascati and KLOE-2 is expected to start data taking at the upgraded DA{Phi}NE {phi}-factory late 2010, with the aim to collect 25 fb{sup -1} at the {phi} peak and it is under discussion the collection of 5 fb{sup -1} between 1 and 2.5 GeV. KLOE data have been used to investigate the properties of the light scalar mesons f{sub 0}(980), a{sub 0}(980) and light pseudoscalar mesons {eta}, {eta}', using {phi} radiative decays. Gamma-gamma interactions allow to investigate also the f{sub 0}(600)/{sigma} meson, observing the reaction e{sup +}e{sup -} into e{sup +}e{sup -}{pi}{sup 0}{pi}{sup 0}; a direct search of the f{sub 0}(600)/{sigma} into {pi}{sup 0}{pi}{sup 0} decay is performed with data taken at a center of mass of 1 GeV, where {phi} decays are suppressed. We present ongoing analysis and final results already published with the full KLOE statistics and the scientific program of KLOE-2 collaboration on hadron physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Implications of first neutrino-induced nuclear recoil measurements in direct detection experiments: Probing nonstandard interaction via CE ν NS

PandaX-4T and XENONnT have recently reported the first measurement of nuclear recoils induced by the B 8 solar neutrino flux, through the coherent elastic neutrino-nucleus scattering ( CE ν NS ) channel. As long anticipated, this is an important milestone for dark matter searches as well as for neutrino physics. This measurement means that these detectors have reached exposures such that searches for low mass, ≲ 10 GeV dark matter cannot be analyzed using the background-free paradigm going forward. It also opens a new era for these detectors to be used as neutrino observatories. In this paper we assess the sensitivity of these new measurements to new physics in the neutrino sector. We focus on neutrino nonstandard interactions (NSI) and show that—despite the still moderately low statistical significance of the signals—these data already provide valuable information. We find that limits on NSI from PandaX-4T and XENONnT measurements are comparable to those derived using combined COHERENT CsI and LAr data. Furthermore, they provide sensitivity to pure τ flavor parameters that are not accessible using stopped-pion or reactor sources. With larger exposures and consequently improvements of statistical uncertainties, forthcoming data from these experiments will provide important, novel results for CE ν NS -related physics. Published by the American Physical Society 2025

Sierra, D. Aristizabal↗
DOE OSTI2021

Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning

Various modeling techniques are used to predict the capacity fade of Li-ion batteries. Algebraic reduced-order models, which are inherently interpretable and computationally fast, are ideal for use in battery controllers, technoeconomic models, and multi-objective optimizations. For Li-ion batteries with graphite anodes, solid-electrolyte-interphase (SEI) growth on the graphite surface dominates fade. This fade is often modeled using physically informed equations, such as square-root of time for predicting solvent-diffusion limited SEI growth, and Arrhenius and Tafel-like equations predicting the temperature and state-of-charge rate dependencies. In some cases, completely empirical relationships are proposed. However, statistical validation is rarely conducted to evaluate model optimality, and only a handful of possible models are usually investigated. This article demonstrates a novel procedure for automatically identifying reduced-order degradation models from millions of algorithmically generated equations via bi-level optimization and symbolic regression. Identified models are statistically validated using cross-validation, sensitivity analysis, and uncertainty quantification via bootstrapping. On a LiFePO 4 /Graphite cell calendar aging data set, automatically identified models utilizing square-root, power law, stretched exponential, and sigmoidal functions result in greater accuracy and lower uncertainty than models identified by human experts, and demonstrate that previously known physical relationships can be empirically "rediscovered" using machine learning.

25 ENERGY STORAGE↗
DOE OSTI2012

A LAGRANGIAN INTEGRATOR FOR PLANETARY ACCRETION AND DYNAMICS (LIPAD)

We present the first particle-based Lagrangian code that can follow the collisional/accretional/dynamical evolution of a large number of kilometer-sized planetesimals through the entire growth process of becoming planets. We refer to it as the Lagrangian Integrator for Planetary Accretion and Dynamics or LIPAD. LIPAD is built on top of SyMBA, which is a symplectic N-body integrator. In order to handle the very large number of planetesimals required by planet formation simulations, we introduce the concept of a tracer particle. Each tracer is intended to represent a large number of disk particles on roughly the same orbit and size as one another and is characterized by three numbers: the physical radius, the bulk density, and the total mass of the disk particles represented by the tracer. We developed statistical algorithms that follow the velocity and size evolution of the tracers due to close gravitational encounters and physical collisions with one another. The tracers mainly dynamically interact with the larger objects (planetary embryos) in the normal N-body way. LIPAD's greatest strength is that it can accurately model the wholesale redistribution of planetesimals due to gravitational interaction with the embryos, which has recently been shown to significantly affect the growth rate of planetary embryos. We verify the code via a comprehensive set of tests that compare our results with those of Eulerian and/or direct N-body codes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

High-precision calculation of the strange nucleon electromagnetic form factors

We report a direct lattice QCD calculation of the strange nucleon electromagnetic form factors G s E and G s M in the kinematic range 0 ≤ Q 2 ≤ 1.2GeV 2 . For the first time, both G s E and G s M are shown to be nonzero with high significance. This work uses closer-to-physical lattice parameters than previous calculations, and achieves an unprecented statistical precision by implementing a recently proposed variance reduction technique called hierarchical probing . We perform model-independent fits of the form factor shapes using the z-expansion and determine the strange electric and magnetic radii and magnetic moment. As a result, we compare our results to parity-violating electron-proton scattering data and to other theoretical studies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

An Applied Strategy for Using Empirical and Hybrid Models in Online Monitoring

The monitoring of plant equipment for failure prediction is one of the key contributors to operation and maintenance (O&M) costs for a nuclear power plant (NPP) because O&M monitoring depends on labor-intensive activities that are required to meet high equipment reliability standards. These activities rely primarily on humans for information gathering, condition diagnosis, and predictive analysis. Online monitoring aims to automate these activities by relying on sensors to replace human information gathering and machine learning to replace human analysis and decision making. To facilitate automated monitoring, a systematic strategy for anomaly detection is needed to optimally use the available sensor data, empirical models, and physics-supported models. This strategy is essential to provide credible reasoning on why and when an empirical (i.e., purely data-driven) versus hybrid (i.e., physics-supported) approach should be used and to determine the ideal mix of these two approaches for a defined anomaly detection scope. The extant methods usually adopt an ad hoc trial-and-error approach that, in addition to being time-consuming and costly, is also highly subjective; it is impacted by the background and the skill set of the personnel making the decisions. Thus, such an approach cannot guarantee an optimum outcome. This represents the motivation of the current research effort, which is focused on devising a scientifically supported strategy for the optimum selection of anomaly detection methods. This report presents a detailed assessment of the main anomaly detection techniques within the empirical or hybrid method streams. Empirical methods include pattern, statistical, and causal inference. Hybrid methods include the use of physics models to train and test data methods, reduce data dimensionality, reduce data-model complexity, augment data, and reduce empirical uncertainty; hybrid methods also include the use of data to tune physics models. The listed techniques within these two streams represent the vast majority of techniques performed for anomaly detection. Using the techniques as outcomes, a strategy was developed to enable a systematic decision-making process to lead to one of these techniques. The strategy is driven by key decision points related to data relevance, simple modeling feasibility, data inference, physics-modeling value, data dimensionality, physics knowledge, method of validation, performance, data availability and suitability for training and testing, cause-effect, entropy inference, and model fitting. Each of these decision points in the strategy is explained in detail in this report with examples, along with the scientific basis behind the decisions and outcomes in common and simplified terminology. The strategy is developed for use by any NPP staff with basic engineering or science knowledge. A user-friendly graphical state flow diagram was also developed as a visual presentation of the strategy. The strategy was tested and demonstrated through two pilot projects for the application of anomaly detection at an NPP. Each pilot had two use cases: an initial case in which certain decisions were made that resulted in one or more empirical techniques and a revised use case where one or more key decisions were modified resulting in using a set of hybrid methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

A global significance evaluation method using simulated events

In High-Energy Physics experiments it is often necessary to evaluate the global statistical significance of apparent resonances observed in invariant mass spectra. One approach to determining significance is to use simulated events to find the probability of a random fluctuation in the background mimicking a real signal. As a high school summer project, we demonstrate a method with Monte Carlo simulated events to evaluate the global significance of a potential resonance with some assumptions. This method for determining significance is general and can be applied, with appropriate modification, to other resonances.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Ten years of CR physics with PAMELA

The satellite borne Pamela instrument is dedicated to the precise and high statistics study of CR fluxes on a four decades energy range. Pamela experiment is the last step of the “Russian-Italian Mission” (RIM) program established in 1992 between several Italian and Russian institutes and with the participation of Sweden and Germany. Designed as a cosmic ray observatory at 1 AU, it extensive program is made possible thanks to the outstanding performance of the instrument, the low energy threshold, the quasi-polar orbit and the 10 years duration of the observation. The physics program pays particular attention to the study of particles and antiparticles fluxes and includes search for dark matter, primordial antimatter, new matter in the Universe, study of cosmic-ray propagation, solar physics and solar modulation, and terrestrial magnetosphere. Very important is the discovery of the anomalous increase of the positron flux at energies higher that 50 GeV (the so called “Pamela anomaly”), and the abrupt spectral hardening of H and He, challenging the current paradigm of cosmic-ray acceleration and propagation in the Galaxy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗